PB2588: PREDICTIVE MODEL OF IN-HOSPITAL CASE FATALITY IN PATIENTS WITH DIFFUSE LARGE B-CELL LYMPHOMA DEVELOPING CORONAVIRUS INFECTION
Authors: Yuri Polyakov, Elena Baryakh, Elena Misyurina, Eugenia Zhelnova, Konstantin Yatskov, Marat Mingalimov, Olga Kochneva, Tatiana Chudnova, Diana Ivanova, Tatyana Tolstykh, Maryana Lysenko
Journal: HemaSphere (2023)

Topic: 30. Infections in hematology (incl. supportive care/therapy) Background: Coronavirus infections (COVID-19) caused by SARS-CoV-2 present new challenges to hematologists, emphasizing the vulnerability of patients with hematologic malignancies, including diffuse large B-cell lymphoma (DLBCL). Aims: Identification of clinical and paraclinical predictors of in-hospital case fatality in patients with DLBCL associated with COVID-19. Methods: Between April 21, 2020, and December 31, 2022, 103 patients with DLBCL (52 men, 51 women) remained under observation by the hematology service of the municipal clinical hospital #52 (Moscow). A multivariable logistic regression analysis was performed to identify predictors of in-hospital case fatality. The binary endpoint of vital status (discharged alive vs death) was used. Statistical significance level of 0.05 was applied. Results: The retrospective analysis included 103 patients, among whom 24 had adverse outcome. Independent variables at the time of hospitalization included sex, age, status of the hematologic condition (remission, progression/relapse, stabilization, de novo diagnosed DLBCL), Charlson comorbidity index, clinical manifestations (fatigue, subfebrile and febrile temperature, cough, dyspnea, diarrhea syndrome), polymerase chain reaction (PCR), COVID-associated immunoglobulins, blood count (lymphocytes, WBC, platelets, hemoglobin), C-reactive protein (CRP), D-dimer, immunoglobulins M and G, albumin, lactate dehydrogenase (LDH), chemotherapy within the month prior to COVID-19 manifestation, exposure to anti-CD20 monoclonal antibodies within the previous 12 months (anti-CD20 mAb), severity of lung damage according to computerized tomography (CT), respiratory failure and chemotherapy line (first, second and subsequent). As the number of included patients was limited, compared to the number of predictors, and to prevent overfitting, a two-step approach was applied to a predictive model. At the first step univariable logistic regression was used to identify variables statistically significantly associated with the outcome, with significance threshold set at p<0.05. The univariable analysis demonstrated statistical significance of the following variables for the hospitalization period: status of the hematologic condition (relapse/progression), PCR positivity, CRP above 6 mg/L, platelets below 100.000 cells/μL, hemoglobin below 120 g/L, albumin below 35 g/L, LDH above 248 U/L, D-dimer above 500 ng/mL, CT lung damage above 50% (CT grade 2 or higher) and grade 2 respiratory failure. Subsequently, the final model was created by minimizing the Akaike information criterion. PCR positivity, CT grade 2, respiratory failure grade 2, hemoglobin, albumin and LDH levels on admission were included in the final model. The area under the ROC curve for the model was 0.959 (95%CI: 0.916;1) (see Figure 1), which is equivalent to a very high quality of outcome prediction. Figure 1.Summary/Conclusion: The suggested predictive model should be used as an additional tool predicting the risk of in-hospital case fatality in patients with DLBCL who develop coronavirus infection caused by SARS-CoV-2. Keywords: B cell lymphoma, COVID-19